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DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker
We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis me...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440714/ https://www.ncbi.nlm.nih.gov/pubmed/37609633 http://dx.doi.org/10.1016/j.isci.2023.107269 |
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author | Wu, Hao-Wei Wu, Jian-De Yeh, Yen-Ping Wu, Timothy H. Chao, Chi-Hong Wang, Weijing Chen, Ting-Wen |
author_facet | Wu, Hao-Wei Wu, Jian-De Yeh, Yen-Ping Wu, Timothy H. Chao, Chi-Hong Wang, Weijing Chen, Ting-Wen |
author_sort | Wu, Hao-Wei |
collection | PubMed |
description | We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis methods, Log rank test, Cox regression and accelerated failure time model (AFT), for users to analyze five types of quantitative features (mRNA, miRNA, lncRNA, protein and methylation of CpG islands) with four survival types, i.e. overall survival, disease-specific survival, disease-free interval, and progression-free interval, in 33 cancer types. Notably, the implemented AFT model provides an alternative method for genes/features which failed the proportional hazard assumption in Cox regression. With the unprecedented number of survival models implemented and high flexibility in analysis, DoSurvive is a unique platform for the identification of clinically relevant targets for cancer researcher and practitioners. DoSurvive is freely available at http://dosurvive.lab.nycu.edu.tw/. |
format | Online Article Text |
id | pubmed-10440714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104407142023-08-22 DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker Wu, Hao-Wei Wu, Jian-De Yeh, Yen-Ping Wu, Timothy H. Chao, Chi-Hong Wang, Weijing Chen, Ting-Wen iScience Article We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis methods, Log rank test, Cox regression and accelerated failure time model (AFT), for users to analyze five types of quantitative features (mRNA, miRNA, lncRNA, protein and methylation of CpG islands) with four survival types, i.e. overall survival, disease-specific survival, disease-free interval, and progression-free interval, in 33 cancer types. Notably, the implemented AFT model provides an alternative method for genes/features which failed the proportional hazard assumption in Cox regression. With the unprecedented number of survival models implemented and high flexibility in analysis, DoSurvive is a unique platform for the identification of clinically relevant targets for cancer researcher and practitioners. DoSurvive is freely available at http://dosurvive.lab.nycu.edu.tw/. Elsevier 2023-07-04 /pmc/articles/PMC10440714/ /pubmed/37609633 http://dx.doi.org/10.1016/j.isci.2023.107269 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wu, Hao-Wei Wu, Jian-De Yeh, Yen-Ping Wu, Timothy H. Chao, Chi-Hong Wang, Weijing Chen, Ting-Wen DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title | DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title_full | DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title_fullStr | DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title_full_unstemmed | DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title_short | DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker |
title_sort | dosurvive: a webtool for investigating the prognostic power of a single or combined cancer biomarker |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440714/ https://www.ncbi.nlm.nih.gov/pubmed/37609633 http://dx.doi.org/10.1016/j.isci.2023.107269 |
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